Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects.
1. Chapter 1. Introduction - p. 1 2. Chapter 2. Surveying, Geomatics, and 3D Reconstruction - p. 13 3. Chapter 3. Scene understanding and model generation - p. 65 4. 3.1. Executive summary - p. 66 5. 3.2. Introduction - p. 66 6. 3.3. Overview of the major as-is modeling platforms - p. 77 7. 3.4. Data preparation - p. 80 8. 3.5. Surface, region, and object detection and segmentation - p. 90 9. 3.6. 3D object fitting - p. 124 10. 3.7. Semantic relationship learning - p. 135 11. 3.8. Using as-designed BIM as prior knowledge - p. 137 12. 3.9. Exploring the potential of deep learning - p. 144 13. 3.10. ICV data management - p. 148 14. 3.11. Conclusion - p. 149 15. 3.12. Discussion questions - p. 150 16. Chapter 4. Use Cases for Owners and Maintainers - p. 169 17. Chapter 5. Use Cases for Architects and Engineers - p. 203 18. Chapter 6. Use Cases for Contractors - p. 267 19. Chapter 7. Use Cases for Subcontractors and Fabricators - p. 315 20. Chapter 8. The Future - p. 363 21. Author Index - p. 371 22. Subject Index - p. 383
Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects.
1. Chapter 1. Introduction - p. 1 2. Chapter 2. Surveying, Geomatics, and 3D Reconstruction - p. 13 3. Chapter 3. Scene understanding and model generation - p. 65 4. 3.1. Executive summary - p. 66 5. 3.2. Introduction - p. 66 6. 3.3. Overview of the major as-is modeling platforms - p. 77 7. 3.4. Data preparation - p. 80 8. 3.5. Surface, region, and object detection and segmentation - p. 90 9. 3.6. 3D object fitting - p. 124 10. 3.7. Semantic relationship learning - p. 135 11. 3.8. Using as-designed BIM as prior knowledge - p. 137 12. 3.9. Exploring the potential of deep learning - p. 144 13. 3.10. ICV data management - p. 148 14. 3.11. Conclusion - p. 149 15. 3.12. Discussion questions - p. 150 16. Chapter 4. Use Cases for Owners and Maintainers - p. 169 17. Chapter 5. Use Cases for Architects and Engineers - p. 203 18. Chapter 6. Use Cases for Contractors - p. 267 19. Chapter 7. Use Cases for Subcontractors and Fabricators - p. 315 20. Chapter 8. The Future - p. 363 21. Author Index - p. 371 22. Subject Index - p. 383
